Unraveling the hidden complexity of cancer through long-read sequencing

作者：Qiuhui Li, Ayse G. Keskus, Justin Wagner, Michal Izydorczyk, Winston Timp, Fritz J. Sedlazeck, Alison P. Klein, Justin M. Zook, Mikhail Kolmogorov, Michael C. Schatz · 发表于：Genome Research · 年份：2025 · DOI：10.1101/gr.280041.124 · 被引用次数：10 · 研究领域：Genomics and Phylogenetic Studies、Cancer Genomics and Diagnostics、CRISPR and Genetic Engineering

Cancer is fundamentally a disease of the genome, characterized by extensive genomic, transcriptomic, and epigenomic alterations. Most current studies predominantly use short-read sequencing, gene panels, or microarrays to explore these alterations; however, these technologies can systematically miss or misrepresent certain types of alterations, especially structural variants, complex rearrangements, and alterations within repetitive regions. Long-read sequencing is rapidly emerging as a transformative technology for cancer research by providing a comprehensive view across the genome, transcriptome, and epigenome, including the ability to detect alterations that previous technologies have overlooked. In this Perspective, we explore the current applications of long-read sequencing for both germline and somatic cancer analysis. We provide an overview of the computational methodologies tailored to long-read data and highlight key discoveries and resources within cancer genomics that were previously inaccessible with prior technologies. We also address future opportunities and persistent challenges, including the experimental and computational requirements needed to scale to larger sample sizes, the hurdles in sequencing and analyzing complex cancer genomes, and opportunities for leveraging machine learning and artificial intelligence technologies for cancer informatics. We further discuss how the telomere-to-telomere genome and the emerging human pangenome could enhance the resol...